An anatomically correct 3D‐printed mouse phantom for magnetic particle imaging studies

Abstract We report anatomically correct 3D‐printed mouse phantoms that can be used to plan experiments and evaluate analysis protocols for magnetic particle imaging (MPI) studies. The 3D‐printed phantoms were based on the Digimouse 3D whole body mouse atlas and incorporate cavities representative of a liver, brain tumor, and orthotopic breast cancer tumor placed in anatomically correct locations, allowing evaluation of the effect of precise doses of MPI tracer. To illustrate their use, a constant tracer iron mass was present in the liver for the breast (200 μgFe) and brain tumor (10 μgFe) model, respectively, while a series of decreasing tracer iron mass was placed in the tumor region. MPI scans were acquired in 2D and 3D high sensitivity and high sensitivity/high resolution (HSHR) modes using a MOMENTUM imager. A thresholding algorithm was used to define regions of interest (ROIs) in the scans and the tracer mass in the liver and tumors was calculated by comparison of the signal in their respective ROI against that of known mass fiducials that were included in each scan. The results demonstrate that this approach to image analysis provides accurate estimates of tracer mass. Additionally, the results show how the limit of detection in MPI is sensitive to the details of tracer distribution in the subject, as we found that a greater tracer mass in the liver cavity resulted in poorer sensitivity in tumor regions. These experiments illustrate the utility of the reported 3D‐printed anatomically correct mouse phantoms in evaluating methods to analyze MPI scans and plan in vivo experiments.

superparamagnetic iron oxide nanoparticle (SPION) tracers. To achieve this, two opposing quasi-static magnetic fields are applied to create a magnetic gradient field with a field-free region (FFR) in the center, while a uniform alternating magnetic field (AMF) is applied to excite the nanoparticles. 2 SPIONs in the FFR respond to the AMF, generating a signal detected by the MPI receive coils. 3 An image is constructed by scanning the FFR over a field of view (FOV). MPI possesses many desirable characteristics for in vivo studies, such as negligible signal from anatomical features, complete tissue penetration, and MPI signal intensity that is proportional to SPION mass, which enables quantification. 1 Since SPIONs can be used to label cells, this makes MPI ideal for cell tracking. 4 Additionally, because SPIONs can be made to release heat that can be used to destroy cancer, MPI can be valuable in magnetic fluid hyperthermia (MFH) 2 studies.
In a typical MPI study, a dose of SPION tracer is administered to Other factors that significantly influence MPI quantification results are the preparation and positioning of known mass fiducials (whether in the same scan or in separate scans), the position and orientation of the subject, and the process of image analysis and processing to estimate tracer mass in a ROI. Most MPI studies to date have focused on proof-of-principle demonstrations of potential applications. However, as the field continues to mature, we expect that increasing attention will be needed to address the role of the above factors on the accuracy and sensitivity of MPI to quantify SPION distribution in living subjects. Because of the large number of factors at play, we hypothesize that MPI-compatible phantoms that allow positioning of precise tracer masses in anatomically correct positions mimicking major organs that accumulate SPION tracers would be immensely valuable to advance the field of MPI.
Historically, phantoms have been used to simulate physiological phenomena, determine appropriate tracer dosages, optimize image quality, and evaluate a system's imaging capabilities. 5 The creation of imaging phantoms has evolved due to recent advances with three-dimensional (3D) printing, which has enabled rapid, low-cost, and reproducible phantom development. 6 3D-printed phantoms for MPI studies have been primarily utilized to evaluate instrument performance [7][8][9] and SPION tracer characteristics 10,11 to ensure reproducibility of experiments in the field.
In addition, phantoms have been used to explore potential biomedical applications of MPI such as magnetic hyperthermia, 12 measurement of blood flow velocity, 13 quantification of vascular stenoses, 14 and stent placement guidance. 15 However, the use of an anatomically correct F I G U R E 1 (a) Rendering of the four-part mouse body assembly with cavities for the 3D-printed mouse liver and brain. A transverse slice separates dorsal parts (A and B) from ventral parts (C and D); a sagittal slice separates lateral pairs (A and C; B and D). (b) Rendering of a 100 mm 3 breast tumor model in wholemouse assembly. Part C was configured to fit breast tumor phantoms of various volumes. (c) Rendering of the liver (red) and brain (gold) inside the mouse. (d) Cross sections of the brain, liver, and breast tumor phantom animal phantom has not been reported for MPI studies. An anatomically correct phantom is desirable because it could mimic the results from in vivo studies and help answer important questions regarding the most suitable MPI data acquisition conditions, image analysis methods, and SPION dose experimental parameters. While MPI already contributes to advancing the ethical principles of T A B L E 1 Dilution series tracer mass for brain tumor and breast tumor phantom studies. Total iron mass was calculated by the 1,10-phenanthroline colorimetric assay for iron quantification including the brain, heart, liver, lungs, stomach, and skin surface, among others. 17 With the incorporation of numerous major organs in anatomically correct locations, phantoms created from the Digimouse atlas, such as the one reported here, can be highly versatile and designed to represent specific disease models.
In this article, we report two 3D-printed mouse phantoms suitable for planning and evaluation of MPI studies. These phantoms were created using the Digimouse atlas and possess anatomically correct locations of liver cavities and breast and brain tumors. These were used to evaluate the effect of signal from nonspecific tracer accumulation in the liver on the detection and quantification of tracer signal in the tumor sites using a previously reported tracer tailored for MPI. 11

| RESULTS
The 3D-printed mouse phantom holds a hollow liver with a 450 mm 3 filling capacity and a brain with two orthogonal cylindrical cavities for capillary tubes loaded with SPION tracer. A flat base was added to the liver for SPION loading convenience and does not contribute to the volume capacity. Due to inconsistencies when 3D printing the hollow liver, the maximum SPION volume loaded in the liver cavity was approximately 375 μL. The four-part mouse body assembly secures the liver and brain in place and allows interchangeability so that a custom right flank for breast tumor studies may be added to the assembly, as illustrated in . The color lookup table range was kept the same for all magnetic particle imaging (MPI) scans and was selected to best visualize the breast tumor signal at low concentrations. The color range may make it difficult to visualize fiducials. Fiducial 1, 2, and 3, contain an iron mass of 2, 2, and 1 μg Fe , respectively, and the liver contains 205 μg Fe dilution series of RL-1 tracer. Table 1 summarizes the iron mass present in the tumor and liver sites for both models. The iron content present in the liver in each model and dilution series was chosen to mimic relevant studies that implement SPION administration. For the brain tumor model, an iron mass of~10 μg Fe was chosen based on a previous study that used MPI to monitor localization of SPION labeled T cell in the brain following adoptive cell transfer (ACT). 4 In that study, 10 7 T cells loaded with approximately 1 pg Fe /cell were administered intravenously and we observed most of the signal in the liver, with a much smaller signal in the brain of mice bearing brain tumors. Thus, the liver mass and brain tumor dilutions were chosen to represent a situation where most of the administered tracer ends up in the liver and a small amount of tracer ends up in the brain tumor. In contrast, an iron mass of~200 μg Fe in the liver for the breast tumor model was chosen to mimic MFH studies, where much larger doses are administered to achieve a significant temperature rise in the tumor. In that case, a mass of~200 μg Fe in the liver could correspond to a case where a dose of 10 mgFe/kg is administered to a 20 g mouse intravenously and most of the tracer accumulates in the liver.
Representative results, consisting of MPI images overlayed with optical images of the phantoms are presented in Figure 2 for the brain tumor model and in Figure 3 for the breast tumor model. We note that the color scale ranges were chosen in Figures 2 and 3 to accentuate the signal from the tumor region in the lowest mass dilution that was visible, thus oversaturating the liver and fiducials in all images.
Furthermore, we note that we assume that a signal with a mean signal-to-noise-ratio (mSNR) greater than 3 indicates a signal that is statistically different from the background 22 and therefore above the limit of detection (LoD).
For the brain tumor model ( Figure S1 in the Supporting Information. Upon inspection of the MPI scans, the signal for the brain tumor ROI with 128.1 ng Fe was below the LoD for both the 2D HS (mSNR = 2.0) and 2D HSHR (mSNR = 1.9) scanning modes. Additionally, in the 3D HS scan mode, the signal for the brain tumor ROI with 128.1 ng Fe was above the LoD (mSNR = 3.8), while the signal for the brain tumor ROI with 64.1 ng Fe was below the LoD (mSNR = 0.8). A representative 3D HS MPI scan coregistered with a CT scan of the mouse phantom is shown in Movie S1, with 2.05 μg Fe in the brain tumor ROI.
For the breast tumor model (  F I G U R E 4 Quantitative analysis of the iron content in the tumor region of interest (ROI) for the brain (top) and breast (bottom) tumor models. Relationship between the known tracer mass and magnetic particle imaging (MPI) calculated tracer mass in the tumor ROI for the brain (a, c) and breast (e, g) tumor models in high-sensitivity (HS) and high-sensitivity/high-resolution (HSHR) scanning modes. Mean signal to noise ratio (mSNR) plots of the tumor ROI for the brain (b, d) and breast (f, h) tumor models in HS and HSHR scanning modes. Some standard deviation bars (n = 3) are smaller than the markers and not clearly visible

| DISCUSSION
The 3D-printed mouse phantoms presented in this study were created to evaluate the effect of MPI signal in the liver on quantification of tracer mass in locations corresponding to brain and breast tumors.
Here, we have considered a signal to be above the LoD when the mSNR is greater than 3. 22 Under these conditions, for the brain tumor While this study presents the use of the 3D-printed mouse phantom for a brain and breast cancer model, this phantom is extremely versatile and can be modified using computer aided design (CAD) software to include or exclude selected organs to simulate various disease models. In this study, the surfaces of the Digimouse, a tessellated 3D anatomical mouse atlas presented in Dogdas et al., were converted to stereolithography (STL) files and modified to create representative phantoms for a breast and brain tumor model. 17 The major components of the phantoms were the liver and the brain and mammary fat pad tumors. This allowed evaluation of the effect of nonspecific accumulation of SPION tracer in the liver on signal detection and quantification in ROI corresponding to brain and breast tumors. However, the Digimouse atlas contains 3D segmentations of several organs in the normal nude male mouse, such as the heart, lungs, stomach, spleen, kidneys, and bladder, to name a few. 17 This allows for creation of anatomically correct phantoms representative of numerous disease models for a variety of applications. Alternative digital mouse atlases have also been developed to model particular sets of organs and mice at different developmental stages. [18][19][20][21] These atlas data sets could be combined and utilized to create anatomically correct phantoms to further tailor these tools to specific applications.
A limitation of this study was that SPION tracer mass in the liver was held constant for each tumor model. Additional work would be needed to correlate liver tracer mass with corresponding sensitivity.
Moreover, the static 3D-printed mouse phantom does not allow for dynamic processes such as breathing or fluid flow, meaning signal due to tracer circulating in the blood cannot be accounted for. As such, these 3D-printed mouse phantoms are suitable to assess situations where MPI scans are acquired after the tracer has cleared from the blood. Previous MPI studies have developed phantoms that enable fluid flow 9,13 and the associated methods could be applied to the anatomically correct mouse phantom reported here in future studies. An additional limitation of the 3D-printed mouse phantom reported here involves the resolution of 3D printers, as it is challenging to print structures smaller than 1 mm. Currently, the resolution of MPI is greater than or equal to 1 mm, 23 alleviating the need for 3D-printed structures smaller than this. However, as new MPI tracers optimized for high resolution are developed there will be a need for alternative approaches that allow for printing phantoms with greater than 1 mm resolution.
Despite these limitations, this study demonstrates the necessity of 3Dprinted phantoms that simulate in vivo experiments to optimize experimental planning and analysis, prior to the use of animals.

| 3D-printed mouse phantom creation
CAD techniques were used to prepare 3D-printable models of mouse anatomy from surface tessellation data. For this purpose, we used the Digimouse 3D whole body mouse atlas reported by Dogdas et al. and which was generated using a combination of CT, PET, x-ray, and cryosection techniques. 17 Surface meshes for the mouse body, liver, and brain were isolated using the Digimouse anatomical tessellation data. 17 Details of the methodology for converting surface tessellations to a 3D-printed model are outlined below. In brief, meshes were reduced and patched, converted to solid parts, edited, and 3D printed as an assembly of a whole mouse body with hollow organs to be loaded with SPION tracer.
Tessellations of mouse anatomy were generated by running the Digimouse Tessellated_Atlas.mat visualization script in MATLAB ® (MathWorks). This Digimouse visualization and volume tessellation code is publicly available and can be found at https://neuroimage.usc. edu/neuro/Digimouse. 17 Meshes were saved as STL files and imported into Autodesk ® MeshMixer (Autodesk Inc) to reduce their triangle number, patch holes, and replace intersecting faces in the mesh.
Using SolidWorks ® (Dassault Systèmes SolidWorks Corporation), these refined mouse body and liver meshes were saved as solid part STL files and subsequently imported into Onshape ® (Onshape Inc) and Blender ® (Blender Foundation) for final design modifications before printing. Figure 5 outlines this conversion process.
The mouse liver was made hollow in Blender ® using a 0.8 mm minimum wall thickness and holes were added to the liver for direct SPION loading. Two holes were added through the mouse brain and suited to hold a capillary tube (1/32 00 ID Â 1/16 00 OD) loaded with SPIONs in a vertical or horizontal position. For this study, SPION loaded capillary tubes were placed in the horizontal position, coincident with the coronal plane. The mouse body, liver, and brain were then imported into Onshape ® and Boolean relationships were used to create a body cavity for each organ. The body was then segmented into a four-piece assembly using sagittal and transverse plane slices to easily insert and remove the organs. In a separate model, a ventral right flank cavity was designed to fit interchangeable hollow spherical breast tumors of various volumes ranging from 10 to 1000 mm 3 for SPION loading and subsequent MPI analysis. The mouse phantom was printed with the Form 3 STL printer (Formlabs Inc) using Clear V4 resin (Formlabs Inc) with layer sizes ranging from 25 to 100 μm.

| Nanoparticle synthesis
RL-1 is a SPION tracer with magnetic properties that have been optimized for MPI and was prepared by the methods described by Liu et al. 11 Briefly, these MPI-tailored SPIONs were synthesized by thermal decomposition of iron oleate with the addition of molecular oxygen and coated with covalently bonded polyethylene glycol. In this study, the batch RL-1C was used, which had a core diameter of 21.4 ± 2.4 nm and hydrodynamic diameter of~55 ± 20 nm. 11

| Data analysis
All MPI scans were analyzed using 3D Slicer (Slicer 4. 10.2), an opensource software for medical imaging analysis. 24 Image registration was performed with the landmark registration tool to colocalize fiducials on 2D and 3D MPI scans with optical images and CT scans, respectively.
Since all fiducials contained Omnipaque, a CT contrast agent, the point source of the fiducial could be visualized and located in the CT scans to properly align with the MPI data. The fiducial placement was kept constant throughout the study. For analysis of MPI scans, the thresholding tool in 3D Slicer was used to create segmentations for each ROI, corresponding to fiducial 1, fiducial 2, fiducial 3, tumor, liver, and background ( Figure S5). Unique thresholding ranges were chosen for each in the corresponding scan mode.
To compare analysis methods, an additional technique using the "Paint" function in 3D Slicer was used to create a defined circle ROI with a 15 mm brush diameter for the brain tumor ROI in the 2D HS scanning mode. The brush diameter was chosen to encompass the MPI signal produced from the brain ROI in the first dilution and used for all subsequent dilutions.
The LoD was evaluated based on the calculation of the mean signal to noise ratio (mSNR) of the tumor ROI. The mSNR was calculated as the ratio of the mean MPI signal intensity of the tumor ROI to the standard deviation of the background ROI in the same scan. The LoD was determined to be the smallest tumor iron mass with a mSNR > 3.
The MPI iron quantification was calculated by considering the background signal and the known iron mass present in the fiducials. First, the total signal in the ROI was calculated using Equation (1).

CONFLICT OF INTEREST
The authors have no conflicts of interest to declare.

DATA AVAILABILITY STATEMENT
The data that support the findings of this study are available from the corresponding author upon reasonable request.